Co-Occurrence Network Analysis to Guide Responsible AI Policy Development in K-12 Education

• In Event: AERA Roundtable Session Sunday 1:45 pm
  In Roundtable Session: AI Meets Educational Leadership

Abstract

This study investigates the landscape of state-level policy implementation regarding artificial intelligence (AI) use in K-12 education. Using co-occurrence analysis on policy documents from state education departments, the study maps out dominant themes, and the spread of AI education initiatives across the U.S. The study found that the states are engaging in AI policy development through varied approaches, often emphasizing data privacy, ethics, and equitable access. The co-occurrence network highlights peripheral concepts as critical focus areas. Additionally, patterns of thematic overlap reveal opportunities for states with active policies to learn from one another's strengths and address common implementation gaps collaboratively. Policymakers can leverage insights from co-occurrence mappings to prioritize underrepresented but impactful topics.

Author

• Qurrat-ul-Ain Rasheed, Georgia State University